Title of article :
Multicontext wavelet-based thresholding segmentation of brain tissues in magnetic resonance images
Author/Authors :
Zhou، نويسنده , , Zhenyu and Ruan، نويسنده , , Zongcai، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2007
Pages :
5
From page :
381
To page :
385
Abstract :
A novel segmentation method based on wavelet transform is presented for gray matter, white matter and cerebrospinal fluid in thin-sliced single-channel brain magnetic resonance (MR) scans. On the basis of the local image model, multicontext wavelet-based thresholding segmentation (MCWT) is proposed to classify 2D MR data into tissues automatically. In MCWT, the wavelet multiscale transform of local image gray histogram is done, and the gray threshold is gradually revealed from large-scale to small-scale coefficients. Image segmentation is independently performed in each local image to calculate the degree of membership of a pixel to each tissue class. Finally, a strategy is adopted to integrate the intersected outcomes from different local images. The result of the experiment indicates that MCWT outperforms other traditional segmentation methods in classifying brain MR images.
Keywords :
image segmentation , wavelets , gray matter , white matter , MAGNETIC RESONANCE IMAGING , cerebrospinal fluid , Brain imaging
Journal title :
Magnetic Resonance Imaging
Serial Year :
2007
Journal title :
Magnetic Resonance Imaging
Record number :
1832422
Link To Document :
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